The present invention relates in general to information processing, and in particular to world modeling using a relationship network that provides communication channels to different entities in the network.
The World Wide Web (Web), as its name suggests, is a decentralized global collection of interlinked information—generally in the form of “pages” that may contain text, images, and/or media content—related to virtually every topic imaginable. Through the contributions of countless users, the Web has grown to become a vast, decentralized treasure trove of information. Finding information in the trove, however, can be difficult.
To make it easier to find information, an industry of search providers (e.g., Yahoo!, MSN, Google) has evolved. A search provider typically maintains a database of Web pages in which the URL (uniform resource locator) of each page is associated with various information (e.g., keywords, category data, etc.) reflecting its content. The search provider also maintains a search server that hosts a search page (or site) on the Web. The search page provides a form into which a user can enter a query that usually includes one or more terms indicative of the user's interest. Once a query is entered, the search server accesses the database and generates a list of “hits,” typically URLs for pages whose content matches keywords derived from the user's query. This list is provided to the user in a search results page, typically including a page title, short abstract, and link for each hit. Since queries can return hundreds, thousands, or even millions of hits, search providers have developed sophisticated algorithms for ranking the hits (i.e., determining an order for displaying hits to the user) in hope that the pages most relevant to a given query will appear near the top of the list. Typical ranking algorithms take into account not only the keywords and their frequency of occurrence but also other information such as the number of other pages that link to the hit page, popularity of the hit page among users, and so on.
The search industry has developed other techniques to enhance the likely relevance of highly ranked hits. For instance, “local” search services have been developed to help users find nearby businesses or other establishments. A local search service generally requires the user to specify a geographic location (e.g., an address, city or postal code) before searching, then gives high rankings to hits related to establishments near the user's location. Similarly, “yellow pages” search services allow a user to search for businesses by name or category (e.g., restaurant, hotel) and geographical location. Such services typically also offer links to maps and/or driving directions to help the user locate a particular business.
Nevertheless, the Web still provides relatively little help to users in completing ordinary tasks, such as locating a good restaurant in an unfamiliar area. A yellow pages search service would provide a list of nearby restaurants or perhaps a list of nearby restaurants specializing in a particular style of food (e.g., Italian, Thai, Indian). The listings might provide links to Web sites for some or all of the restaurants, via which the user can obtain basic factual information about a restaurant such as hours, price range, or sample menus.
This information, however, is insufficient for making an optimum choice. A person selecting a restaurant usually wants to consider not only what dishes are served but also whether the food is tasty, the service friendly, or the atmosphere conducive to some personal preference. Such subjective information is usually provided in restaurant reviews, but conventional yellow pages listings generally do not provide links to opinions from secondary sources. To obtain such information, the user would generally need to pick a particular restaurant from the yellow pages listing and execute a separate search on the restaurant name, perhaps adding the term “review” or a similar keyword, then look through the search results to identify which ones actually contain reviews of the restaurant in question. To compare reviews of different restaurants, multiple searches would generally be required. Since this process can become tedious, users often decide not to even try to make an informed choice.
Similarly, users attempting to use the Web to do a variety of other everyday tasks—including selecting a contractor for home repairs, researching and purchasing consumer goods, making travel plans, and so on—generally face the prospect of performing multiple searches and manually filtering the results to find helpful information. As a result, many users are unable to exploit the trove of existing information.
In addition, users who want to share their experiences and opinions about restaurants, contractors, products, vacation experiences or other real-world concerns find it difficult to do so. In principle, anyone can publish content on the Web, but in practice it is unlikely that a Web page commenting on a topic would be found by other users, even users looking for comments on that topic.
Therefore, it would be desirable to provide information models that enable the user to efficiently collect and review information related to an object of interest.